Enhancing accurate data collection in mass fatality kinship identifications: lessons learned from Hurricane Katrina
Sandra Donkervoort1, Siobhan M Dolan, Michelle Beckwith
1Joan H. Marks Graduate Program in Human Genetics, Sarah Lawrence College, Bronxville, NY, USA. s-donkervoort@northwestern.edu
Forensic Science International. Genetics
|December 17, 2008
Summary
This study analyzes the effectiveness of the Family and/or Donor Reference Collection (FDRC) form for mass fatality DNA identification. An improved form can enhance accuracy and streamline the kinship DNA identification process.
Area of Science:
- Forensic Science
- Genetics
- Disaster Victim Identification
Background:
- Mass fatality DNA identification relies on direct matching and kinship analysis.
- Accurate documentation of biological relationships is crucial for effective identification.
- Previous mass fatality events highlighted the importance of standardized documentation forms.
Purpose of the Study:
- To analyze the effectiveness of the Family and/or Donor Reference Collection (FDRC) form used in Hurricane Katrina.
- To propose an improved sample collection form for kinship and donor reference samples.
- To enhance the accuracy and efficiency of DNA kinship identification processes.
Main Methods:
- Analysis of the FDRC form's performance during Hurricane Katrina identification efforts.
- Review of lessons learned from 9/11 and Tsunami identification efforts in form development.
- Proposal of an improved sample collection form based on data analysis.
Main Results:
- The FDRC form's effectiveness in documenting relationships for kinship analysis was evaluated.
- Inaccurately documented information can impede the DNA identification process.
- An improved form can lead to more accurate data collection.
Conclusions:
- The FDRC form's utility in Hurricane Katrina was assessed.
- An enhanced sample collection form can streamline DNA kinship identification.
- Improving data collection accuracy reduces the burden on resources during mass fatality events.
Related Concept Videos
Applications of GIS: Disaster Management and Emergency Response
Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
Data Collection III
The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the patient.
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the patient.
Data Collection I
Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of data...
Kaplan-Meier Approach
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...

